Conditional Choice Probability Estimation of Dynamic Discrete Choice Models With Unobserved Heterogeneity

By P. Arcidiacono, Robert A. Miller. 2011

411 citations recorded by the source corpus.

Subfields: Economics and Econometrics, Food Science, Marketing

View Paper: https://www.semanticscholar.org/paper/4be9a882a0d4b79917d3f92c8a9ace0e4ee4d101

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Citations in the corpus

Artificial intelligence as structural estimation: Deep Blue, Bonanza, and AlphaGo (2017, background): “Artificial intelligence (AI) has achieved human-like performance in a growing number of tasks, such as visual recognition and natural language processing.(1) The classical games of chess, shogi (Japanese chess), and Go were once thought to be too complicated and intractable for AI, but computer scie”
Estimation of Dynamic Discrete Choice Models in Continuous Time with an Application to Retail Competition (2016, positive): “Both the hazards and type probabilities are estimated in the first stage using the EM algorithm as in Arcidiacono and Miller (2011). Bayes’ rule gives the probability of marketm being in unobserved state z given the data.”
Nonlinear Panel Data Estimation via Quantile Regressions (2015, methodology): “Model (6) may easily be modified to allow for more general interactions between observables and unobservables, thus permitting the effects of covariates to be heterogeneous at different quantiles.”
Semiparametric Inference in Dynamic Binary Choice Models, Second Version (2014, methodology): “to estimation of models with time-variant unobserved heterogeneity considered by Arcidiacono and Miller (2011). Generalizing our framework to multinomial choice models is an important direction for future research.”
The New Economics of Equilibrium Sorting and Policy Evaluation Using Housing Markets (2013, methodology): “Bishop (2009) adapts the two-step approach described by Arcidiacono and Miller (2011) to the Kennan-Walker interstate sorting context and proposes a forward looking model for 58 Roback’s model is most commonly used to calculate “quality-of-life” indices.”
A practitioners' guide to gravity models of international migration (2016, positive): “These simple observations call for rewriting location-specific utility in a way that explicitly reflects the sequential nature of the location decision problem, following the literature on dynamic discrete choice models (Artuc et al., 2010; Arcidiacono and Miller, 2011; Kennan and Walker, 2011):”
Discretizing Unobserved Heterogeneity (2017, methodology): “The intuition for this choice is that, for K = K̂ given by (4) with γ = 1, the within-group variation in hi is of the same order as the noise level V̂h.”
Cupid’s Invisible Hand: Social Surplus and Identification in Matching Models (2015, positive): “Bajari and Fox (2013) applied this approach to spectrum auctions. Fox, Yang, and Hsu (2018) focus on identifying the complementarity between unobservable characteristics. Gualdani and Sinha (2019) study partial identification issues in nonparametric matching models. The literature on markets with no”
The Effects of Rent Control Expansion on Tenants, Landlords, and Inequality: Evidence from San Francisco (2019, positive): “Hotz and Miller (1993)) relating conditional value functions to conditional choice probabilities pt (x|θt−1): pt (x|θt−1) = exp (vt (x, θt−1)) ∑ x′ exp (vt (x ′, θt−1)) .”